Temporally and spatially resolved molecular profiling in fingerprint analysis using indium vanadate nanosheets-assisted laser desorption ionization mass spectrometry

This study presents the first-ever synthesis of samarium-doped indium vanadate nanosheets (IVONSs:Sm) via microemulsion-mediated solvothermal method. The nanosheets were subsequently utilized as a nano-matrix in laser desorption/ionization mass spectrometry (LDI-MS). It was discovered that the as-synthesized IVONSs:Sm possessed the following advantages: improved mass spectrometry signal, minimal matrix-related background, and exceptional stability in negative-ion mode. These qualities overcame the limitations of conventional matrices and enabled the sensitive detection of small biomolecules such as fatty acids. The negative-ion LDI mechanism of IVONSs:Sm was examined through the implementation of density functional theory simulation. Using IVONSs:Sm-assisted LDI-MS, fingerprint recognitions based on morphology and chemical profiles of endogenous/exogenous compounds were also achieved. Notably, crucial characteristics such as the age of an individual's fingerprints and their physical state could be assessed through the longitudinal monitoring of particular biomolecules (e.g., ascorbic acid, fatty acid) or the specific biomarker bilirubin glucuronide. Critical information pertinent to the identification of an individual would thus be facilitated by the analysis of the compounds underlying the fingerprint patterns.

Hydrogel-enzyme micropatch array format for chemical mapping: A proof of concept

Conventional sensing methods report on concentrations of analytes in a single point of sampled medium or provide an average value. However, distributions of substances on surfaces of sampled objects often exhibit intricate inhomogeneities. In order to obtain snapshots of the chemical distributions on surfaces, we have developed enzyme-loaded hydrogel arrays (5 × 5 and 10 × 10). The acrylic 10 × 10 array base contains 100 holes, which are filled with agarose hydrogel containing assay enzymes and substrates. Such arrays can be exposed to the analyzed surfaces to collect minute amounts of analytes. Following a brief incubation, they are subsequently visualized in a custom-built array reader device. The reader incorporates a light-emitting diode-based light source, miniature camera, and Raspberry Pi single-board computer. Two Python programs capture and analyze the images of the array to extract pixel saturation values corresponding to individual hydrogel micropatches. The method has been thoroughly optimized for mapping of glucose and lactic acid. The optimized parameters were: contact time, agarose concentration, substrate concentration, enzyme concentration ratio, and enzyme concentration. The array biosensor was further tested by mapping glucose distribution in fruit/vegetable cross-sections (apple, guava, and cucumber) and lactic acid distribution in cheese. We think that this new hydrogel-based chemical mapping method can find applications in studies related to food science, plant physiology, clinical chemistry, and forensics; wherever the distributions of analytes on the tested surfaces need to be assessed.

In vivo secondary structural analysis of Influenza A virus genomic RNA

Influenza A virus (IAV) is a respiratory virus that causes epidemics and pandemics. Knowledge of IAV RNA secondary structure in vivo is crucial for a better understanding of virus biology. Moreover, it is a fundament for the development of new RNA-targeting antivirals. Chemical RNA mapping using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) coupled with Mutational Profiling (MaP) allows for the thorough examination of secondary structures in low-abundance RNAs in their biological context. So far, the method has been used for analyzing the RNA secondary structures of several viruses including SARS-CoV-2 in virio and in cellulo. Here, we used SHAPE-MaP and dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) for genome-wide secondary structure analysis of viral RNA (vRNA) of the pandemic influenza A/California/04/2009 (H1N1) strain in both in virio and in cellulo environments. Experimental data allowed the prediction of the secondary structures of all eight vRNA segments in virio and, for the first time, the structures of vRNA5, 7, and 8 in cellulo. We conducted a comprehensive structural analysis of the proposed vRNA structures to reveal the motifs predicted with the highest accuracy. We also performed a base-pairs conservation analysis of the predicted vRNA structures and revealed many highly conserved vRNA motifs among the IAVs. The structural motifs presented herein are potential candidates for new IAV antiviral strategies.

A dual AE-GAN guided THz spectral dehulling model for mapping energy and moisture distribution on sunflower seed kernels

Energy and moisture contents are important food chemical attributes. In the current study, a nondestructive Terahertz (THz) time-domain imaging system was first time used for evaluating the energy and moisture distributions of sunflower seed kernels inside shells. For this task, a dual autoencoders (AE)-generative adversarial nets (GAN) spectral dehulling semi-supervised model was developed. The model could automatically learn the kernel information from the latent representations of the spectra of the intact seeds through adversarial learning to achieve feature disentanglement. Results indicated that the generated kernel images had similar features to the original kernel images and high-quality chemical distribution maps for energy and moisture contents of sunflower seed kernels inside shells were successfully obtained. As the current method took the advantage of the characteristics of THz imaging and selected a suitable deep learning algorithm, it has the potential to generalize for imaging other chemical substances of other dry shelled seeds or biological samples (moisture content and thickness below 15% and 5 mm, respectively).

Chemical mapping of tire and road wear particles for single particle analysis

Tire and road wear particles (TRWP), which are comprised of polymer-containing tread with pavement encrustations, are generated from friction between the tire and the road. Similar to environmentally dispersed microplastic particles (MP), the fate of TRWP depends on both the mass concentration as well as individual particle characteristics, such as particle diameter and density. The identification of an individual TRWP in environmental samples has been limited by inherent characteristics of black particles, which interfere with the spectroscopic techniques most often used in MP research. The purpose of this research was to apply suitable analytical techniques, including scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM/EDX) mapping and time-of-flight secondary ion mass spectrometry (ToF-SIMS) mapping, to characterize the specific physical and chemical properties of individual TRWP. Detailed elemental and organic surface maps were generated for numerous samples including bulk tread material, cryogenically milled tire tread particles, and TRWP generated from two separate road simulator methods. Key physical and chemical characteristics of TRWP for single particle identification included (1) elongated/round shape with variable amounts of mineral encrustation, (2) elemental surface characteristics including co-localization of (S + Zn/Na) ± (Si, K, Mg, Ca, and Al), and (3) co-localization of organic surface markers, such as C₆H₅⁺ and C₇H₇⁺. Comparisons of TRWP with other polymeric (polystyrene) and non-polymeric (carbon black) particle types demonstrated that a combination of physical and chemical markers is necessary to identify TRWP. Addition of a density separation step to the single particle analysis techniques allowed for the determination of average primary TRWP particle size (34 μm by number distribution and 49 μm by volume distribution) and aspect ratio (65% of TRWP with an aspect ratio > 1.5). The use of chemical mapping techniques, such as SEM/EDX and/or ToF-SIMS mapping as demonstrated herein, can support future research efforts that aim to identify complex MP.

Near-infrared hyperspectral imaging (NIR-HSI) and normalized difference image (NDI) data processing: An advanced method to map collagen in archaeological bones

In the present study, an innovative and highly efficient near-infrared hyperspectral imaging (NIR-HSI) method is proposed to provide spectral maps able to reveal collagen distribution in large-size bones, also offering semi-quantitative estimations. A recently introduced method for the construction of chemical maps, based on Normalized Difference Images (NDI), is declined in an innovative approach, through the exploitation of the NDI values computed for each pixel of the hyperspectral image to localize collagen and to extract information on its content by a direct comparison with known reference samples. The developed approach addresses an urgent issue of the analytical chemistry applied to bioarcheology researches, which rely on well-preserved collagen in bones to obtain key information on chronology, paleoecology and taxonomy. Indeed, the high demand for large-sample datasets and the consequent application of a wide variety of destructive analytical methods led to the considerable destruction of precious bone samples. NIR-HSI pre-screening allows researchers to properly select the sampling points for subsequent specific analyses, to minimize costs and time and to preserve integrity of archaeological bones (which are available in a very limited amount), providing further opportunities to understand our past.

Reflection FTIR spectroscopy for the study of historical bowed string instruments: Invasive and non-invasive approaches

A micro-sample detached from a historical bowed string instrument represents a valuable record of the materials used by the great Masters of violin-making art. It allows researchers to collect a wealth of information and to disclose - at least partially - their procedures for finishing and varnishing. In the present work, a set of four cross-sectioned micro-samples - collected from well-preserved bowed string instruments made by Antonio Stradivari and Lorenzo Storioni - are investigated by Synchrotron Radiation (SR) FTIR micro-spectroscopy in reflection mode. SR-FTIR spectra are discussed both as point analysis and as univariate and multivariate chemical maps. The same cross-sections are also investigated by optical microscopy under UV light and SEM-EDX. Moreover, data obtained directly from the musical instruments by a non-invasive approach employing a portable reflection FTIR spectrometer are also considered. FTIR investigation of the cross-sections is a challenging task for such brittle and complex layered micro-samples. Nevertheless, the high intensity of the analytical SR beam used in reflection geometry allowed us to obtain informative FTIR spectra and to fully preserve the integrity of the samples. Both the non-invasive and the micro-invasive reflection FTIR approaches can reveal the materials spread on the wood surface to finish the musical instruments. The fingerprint of Lorenzo Storioni's production around 1790 emerged from the study of the cross-sectioned samples, definitely different from the technique of Stradivari.

An in-depth study of cheese ripening by means of NIR hyperspectral imaging: Spatial mapping of dehydration, proteolysis and lipolysis

Cheese represents one of the most complex food matrices, for the high number of factors contributing to the chemical composition, and so its evaluation represents an important analytical challenge. The present study describes an innovative and non-destructive analytical approach, based on hyperspectral imaging in the near-infrared region (HSI-NIR) and multivariate pattern recognition, to study and monitor the extent - spatial and temporal - of biochemical phenomena responsible for cheese ripening. NIR spectral bands characterising dehydration, proteolysis and lipolysis were individuated and studied by exploiting a representative sample set of characteristic cheeses. The information obtained was employed to develop score maps based on principal component analysis (PCA), which permitted to monitor and visualise the ripening of Formaggetta, a commercial semi-hard cheese typical of Liguria, an Italian region, providing a deep understanding of the evolution of dehydration, proteolysis and lipolysis during the maturation period that precedes the placing on the market.

Raman Imaging of Plant Cell Walls

Raman imaging is a microspectroscopic approach revealing the chemistry and structure of plant cell walls in situ on the micro- and nanoscale. The method is based on the Raman effect (inelastic scattering) that takes place when monochromatic laser light interacts with matter. The scattered light conveys a change in energy that is inherent of the involved molecule vibrations. The Raman spectra are thus characteristic for the chemical structure of the molecules and can be recorded spatially ordered with a lateral resolution of about 300 nm. Based on thousands of acquired Raman spectra, images can be assessed using univariate as well as multivariate data analysis approaches. One advantage compared to staining or labeling techniques is that not only one image is obtained as a result but different components and characteristics can be displayed in several images. Furthermore, as every pixel corresponds to a Raman spectrum, which is a kind of "molecular fingerprint," the imaging results should always be evaluated and further details revealed by analysis (e.g., band assignment) of extracted spectra. In this chapter, the basic theoretical background of the technique and instrumentation are described together with sample preparation requirements and tips for high-quality plant tissue sections and successful Raman measurements. Typical Raman spectra of the different plant cell wall components are shown as well as an exemplified analysis of Raman data acquired on the model plant Arabidopsis. Important preprocessing methods of the spectra are included as well as single component image generation (univariate) and spectral unmixing by means of multivariate approaches (e.g., vertex component analysis).

Comprehensive analysis of renal arsenic accumulation using images based on X-ray fluorescence at the tissue, cellular, and subcellular levels

Exposure to arsenic (As) through drinking water results in accumulation of As and its methylated metabolites in several organs, promoting adverse health effects, particularly potential development of cancer. Arsenic toxicity is a serious global health concern since over 200 million people are chronically exposed worldwide. Abundant biochemical and epidemiological evidence indicates that the kidney is an important site of uptake and accumulation of As, and mitochondrial damage plays a crucial role in arsenic toxicity. However, non-destructive analyses and in situ images revealing As fate in renal cells and tissue are scarce or almost non-existent. In this work, kidney tissue from exposed rats was analyzed by EDXRF (Energy dispersive X-ray fluorescence), micro-SRXRF (micro X-ray Fluorescence using Synchrotron Radiation), SRTXRF (SRXRF in total reflection condition), SEM-EDX (Scanning Electron Microscope in combination with EDXRF) and SRXRF-XANES (SRXRF in combination with X-ray Absorption Near Edge Spectroscopy). Our results provide evidence of renal cortex distribution of As with periglomerular localization, co-localization of S, Cu and As in subcellular compartment of proximal tubule cells, mono-methylarsonous acid accumulation in renal cortex mitochondria, and altered subcellular concentration and distribution of other elements.

Histopathology mapping of biochemical changes in diffuse axonal injury by FTIR micro-spectroscopy

The diagnosis of diffuse axonal injury (DAI) is an important task in forensic pathology and clinical medicine. This study aimed to explore the use of Fourier transform infrared spectroscopy (FTIR) to detect DAI. The DAI area of the rat model was detected point by point by the FTIR-mapping system. Infrared spectral data of DAI were obtained by selecting the amide A band, CH₃ symmetric stretching, collagen triple-helix structure and asymmetric stretching vibrational frequency of nucleic acid and phospholipid PO₂ as the target peak positions. The system can automatically draw infrared spectral color pathological images. In the DAI group, the amide A protein secondary amine N-H stretching vibration and the collagen triple-helix structure of the high-absorption area were consistent with the DAI area confirmed by the silver and β-APP staining. The CH₃ symmetric stretching, nucleic acid and phospholipid PO₂ symmetric stretching vibration absorption spectra showed no significant differences between the experimental and verification groups. The FTIR-mapping technique can visually express the molecular characteristics of DAI, which is expected to be applied to the pathological diagnosis of DAI.

Quantitative drinking water arsenic concentrations in field environments using mobile phone photometry of field kits

Arsenic (As) groundwater contamination is common yet spatially heterogeneous within most environments. It is therefore necessary to measure As concentrations to determine whether a water source is safe to drink. Measurement of As in the field involves using a test strip that changes color in the presence of As. These tests are relatively inexpensive, but results are subjective and provide binned categorical data rather than exact determinations of As concentration. The goal of this work was to determine if photos of field kit test strips taken on mobile phone cameras could be used to extract more precise, continuous As concentrations. As concentrations for 376 wells sampled from Araihazar, Bangladesh were analyzed using ICP-MS, field kit and the new mobile phone photo method. Results from the field and lab indicate that normalized RGB color data extracted from images were able to accurately predict As concentrations as measured by ICP-MS, achieving detection limits of 9.2μg/L, and 21.9μg/L for the lab and field respectively. Data analysis is most consistent in the laboratory, but can successfully be carried out offline following image analysis, or on the mobile phone using basic image analysis software. The accuracy of the field method was limited by variability in image saturation, and variation in the illumination spectrum (lighting) and camera response. This work indicates that mobile phone cameras can be used as an analytical tool for quantitative measures of As and could change how water samples are analyzed in the field more widely, and that modest improvements in the consistency of photographic image collection and processing could yield measurements that are both accurate and precise.

Elucidation of penetration enhancement mechanism of Emu oil using FTIR microspectroscopy at EMIRA laboratory of SESAME synchrotron

It has been proposed that Emu oil possesses skin permeation-enhancing effect. This study aimed to address its possible penetration enhancement mechanism(s) using IR microscopy, in accordance with LPP theory. The penetration of Emu oil through the layers of human skin was accomplished by monitoring oil-IR characteristic feature at 3006cm^-1. The unsaturated components of Emu oil accumulated at about 270μm depth of skin surface. The interaction of Emu oil with lipid and protein constituents of SC was investigated in comparison with a commonly used enhancer, IPM. Inter-sample spectral differences were identified using PCA and linked with possible enhancement mechanisms. Emu oil treatment caused a change in the slope of the right contour of amide I band of the protein spectral range. This was also clear in the second derivative spectra where the emergence of a new shoulder at higher frequency was evident, suggesting disorganization of keratin α-helix structure. This effect could be a result of disruption of some hydrogen bonds in which amide CO and NH groups of keratin are involved. The low intensity of the emerged shoulder is also in agreement with formation of weaker hydrogen bonds. IPM did not affect the protein component. No conclusions regarding the effect of penetration enhancers on the SC lipids were obtained. This was due to the overlap of the endogenous (skin) and exogenous (oil) CH stretching and scissoring frequencies. The SC carbonyl stretching peak disappeared as a result of IPM treatment which may reflect some degree of lipid extraction.

Improving Sensitivity and Reproducibility of SERS Sensing in Microenvironments Using Individual, Optically Trapped Surface-Enhanced Raman Spectroscopy(SERS) Probes

Surface-enhanced Raman spectroscopy (SERS) sensors offer many advantages for chemical analyses, including the ability to provide chemical specific information and multiplexed detection capability at specific locations. However, to have operative SERS sensors for probing microenvironments, probes with high signal enhancement and reproducibility are necessary. To this end, dynamic enhancement of SERS (i.e., in-situ amplification of signal-to-noise and signal-to-background ratios) from individual probes has been explored. In this paper, we characterize the use of optical tweezers to amplify SERS signals as well as suppress background signals via trapping of individual SERS active probes. This amplification is achieved through a steady presence of a single "hot" particle in the focus of the excitation laser. In addition to increases in signal and concomitant decreases in non-SERS backgrounds, optical trapping results in an eightfold increase in the stability of the signal as well. This enhancement strategy was demonstrated using both single and multilayered SERS sub-micron probes, producing combined signal enhancements of 24-fold (beyond the native 10⁶ SERS enhancement) for a three-layered geometry. The ability to dynamically control the enhancement offers the possibility to develop SERS-based sensors and probes with tailored sensitivities. In addition, since this trapping enhancement can be used to observe individual probes with low laser fluences, it could offer particular interest in probing the composition of microenvironments not amenable to tip-enhanced Raman spectroscopy or other scanning probe methods (e.g., intracellular analyses, etc.).

Topochemical Analysis of Cell Wall Components by TOF-SIMS

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is a recently developing analytical tool and a type of imaging mass spectrometry. TOF-SIMS provides mass spectral information with a lateral resolution on the order of submicrons, with widespread applicability. Sometimes, it is described as a surface analysis method without the requirement for sample pretreatment; however, several points need to be taken into account for the complete utilization of the capabilities of TOF-SIMS. In this chapter, we introduce methods for TOF-SIMS sample treatments, as well as basic knowledge of wood samples TOF-SIMS spectral and image data analysis.

Traditional Chemical Mapping of RNA Structure In Vitro and In Vivo

Chemical probing is often used to gain knowledge on the secondary and tertiary structures of RNA molecules either free or engaged in complexes with ligands. The method monitors the reactivity of each nucleotide towards chemicals of various specificities reflecting the hydrogen bonding environment of each nucleotide within the RNA molecule. In addition, information can be obtained on the binding site of a ligand (noncoding RNAs, protein, metabolites), and on RNA conformational changes that accompanied ligand binding or perturbation of the environmental cues. The detection of the modifications can be obtained either by using end-labeled RNA molecules or by primer extension using reverse transcriptase. The goal of this chapter is to provide the reader with an experimental guide to probe the structure of RNA in vitro and in vivo with the most suitable chemical probes.

Modeling complex RNA tertiary folds with Rosetta

Reliable modeling of RNA tertiary structures is key to both understanding these structures' roles in complex biological machines and to eventually facilitating their design for molecular computing and robotics. In recent years, a concerted effort to improve computational prediction of RNA structure through the RNA-Puzzles blind prediction trials has accelerated advances in the field. Among other approaches, the versatile and expanding Rosetta molecular modeling software now permits modeling of RNAs in the 100-300 nucleotide size range at consistent subhelical (~1 nm) resolution. Our laboratory's current state-of-the-art methods for RNAs in this size range involve Fragment Assembly of RNA with Full-Atom Refinement (FARFAR), which optimizes RNA conformations in the context of a physically realistic energy function, as well as hybrid techniques that leverage experimental data to inform computational modeling. In this chapter, we give a practical guide to our current workflow for modeling RNA three-dimensional structures using FARFAR, including strategies for using data from multidimensional chemical mapping experiments to focus sampling and select accurate conformations.

Identification of the chemical form of sulfur compounds in the Japanese pink coral (Corallium elatius) skeleton using μ-XRF/XAS speciation mapping

The distributions and chemical forms of sulfur compounds in the skeleton of Japanese pink coral (Corallium elatius) were investigated using X-ray spectroscopic techniques combined with micro-focused soft X-ray radiation. Microscopic X-ray fluorescence/soft X-ray photoabsorption (μ-XRF/XAS) speciation mapping clarified that sulfate is the primary species in the coral skeleton, with minor amounts of organic sulfur, whereas both sulfate and organic sulfur coexist in coenenchyme. Analysis of the post-edge region of the XAS spectra confirmed that sulfate ions in the coral skeleton are mainly in the form of gypsum-like inorganic sulfate substituting for the carbonate ions in the calcite skeleton. The sulfate concentration was negatively correlated with the magnesium concentration and positively correlated with that of phosphorus. Speciation mapping of sulfate in the coral skeleton showed clear fluctuations with sulfate concentrations being higher at dark bands, whereas the small amount of organic sulfur had unclear dark/bright bands. These results suggest that the little organic sulfur that is present is contained in the organic matter embedded in the biocrystal of coral skeleton.

A locally convoluted cluster model for nucleosome positioning signals in chemical map

Nucleosome is the fundamental packing unit of DNA in eukaryotic cells, and its positioning plays a critical role in regulation of gene expression and chromosome functions. Using a recently developed chemical mapping method, nucleosomes can be potentially mapped with an unprecedented single-base-pair resolution. Existence of overlapping nucleosomes due to cell mixture or cell dynamics, however, causes convolution of nucleosome positioning signals. In this paper, we introduce a locally convoluted cluster model and a maximum likelihood deconvolution approach, and illustrate the effectiveness of this approach in quantification of the nucleosome positional signal in the chemical mapping data.

Chemical mapping of DNA and counter-ion content inside phage by energy-filtered TEM

Double-stranded DNA in many bacterial viruses (phage) is strongly confined, which results in internal genome pressures of tens of atmospheres. This pressure is strongly dependent on local ion concentration and distribution within the viral capsid. Here, we have used electron energy loss spectroscopy (EELS), energy-filtered TEM (EFTEM) and X-ray energy dispersive spectroscopy to provide such chemical information from the capsid and the phage tail through which DNA is injected into the cell. To achieve this, we have developed a method to prepare thin monolayers of self-supporting virus/buffer films, suitable for EELS and EFTEM analysis. The method is based on entrapment of virus particles at air-liquid interfaces; thus, the commonly used method of staining by heavy metal salts can be avoided, eliminating the risk for chemical artifacts. We found that Mg(2 + ) concentration was approximately 2-4 times higher in the DNA-filled capsid than in the surrounding TM buffer (containing 10 mM Mg(2 + )). Furthermore, we also analyzed the DNA content inside the phage tail by mapping phosphorus and magnesium.